scholarly journals Schumann resonance frequency variations observed in magnetotelluric data recorded from Garhwal Himalayan region India

2009 ◽  
Vol 27 (9) ◽  
pp. 3497-3507 ◽  
Author(s):  
R. Chand ◽  
M. Israil ◽  
J. Rai

Abstract. Schumann resonance (SR) frequency variation has been studied using Magnetotelluric (MT) data recorded in one of the world's toughest and generally inaccessible Himalayan terrain for the first time in the author's knowledge. The magnetotelluric data, in the form of orthogonal time varying electric and magnetic field components (Ex, Ey, Bx and By), recorded during 10 March–23 May 2006, in the Himalayan region, India, at elevations between 1228–2747 m above mean sea level (amsl), were used to study the SR frequency variation. Electromagnetic field components, in the form of time series, were recorded at 64 Hz sampling frequency at a site located away from the cultural noise. Spectral analysis of time series data, at a frequency resolution of 0.03 Hz, has been performed using Fast Fourier Transform (FFT) algorithm. Spectral stabilization in three Schumann resonance modes is achieved by averaging the power spectral magnitude of 32 data segments, each with 2048 sample data. Amplitude variation in the Schumann resonance frequency associated with day-night, sunrise and terminator effect was observed. Average diurnal variation in the first three Schumann resonance frequencies associated with magnetic field components is presented. The maximum frequency variation of about 0.3, 0.4 and 0.7 Hz was observed in the first, second and third mode, respectively. The frequency variations observed in electric and magnetic field components also show phase shift and varying attenuation. The SR frequency variation has been used to define the ionospheric electron density variation in the Himalayan region, India.

2013 ◽  
Vol 20 (1) ◽  
pp. 11-18 ◽  
Author(s):  
S. Prabin Devi ◽  
S. B. Singh ◽  
A. Surjalal Sharma

Abstract. A test for deterministic dynamics in a time series data, namely the 0–1 test (Gottawald and Melbourne, 2004, 2005), is used to study the magnetospheric dynamics. The data, corresponding to the same time period, of the auroral electrojet index AL and the magnetic field component Bz of the solar wind magnetic field measured at 1 AU are used to compute the parameter K, which is zero for non-chaotic and unity for chaotic systems. For the magnetosphere and also for the turbulent solar wind, K has values corresponding to a nonlinear dynamical system with chaotic behaviour. This result is consistent with the Lyapunov exponents computed from the same time series data.


2005 ◽  
Vol 23 (7) ◽  
pp. 2559-2564 ◽  
Author(s):  
V. Grimalsky ◽  
S. Koshevaya ◽  
A. Kotsarenko ◽  
R. Perez Enriquez

Abstract. A penetration of electric and magnetic fields of the first global electromagnetic ELF resonance into the ionosphere in the cavity Earth-ionosphere is investigated numerically. It is shown that a penetration height for magnetic components is 2–3 times greater than for electric components and it depends essentially on the value of the geomagnetic field and its orientation with respect to the normal to the Earth's surface. A penetration height for the electric field is about 50÷70 km, and for the magnetic field it is 120÷240 km. An influence of variations of the conductivity of the ionosphere at the daytime and nighttime and under different solar activity on a penetration of the fields of the first Schumann resonance has been investigated. Keywords. Electromagnetics (Guided waves) – Ionosphere (Ionosphere-atmosphere interactions; Wave propagation)


2013 ◽  
Author(s):  
Stephen J. Tueller ◽  
Richard A. Van Dorn ◽  
Georgiy Bobashev ◽  
Barry Eggleston

Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.


2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai

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